Communication Scheduling and Buslet Synthesis for Low-Interconnect HLS Designs. - Enzo Tartaglione; Shantanu Dutt (ICCAD, 2015)

On the role of synaptic stochasticity in training low-precision neural networks. - Carlo Baldassi; Federica Gerace; Hilbert J. Kappen; Carlo Lucibello; Luca Saglietti; Enzo Tartaglione; Riccardo Zecchina (CoRR, 2017)

Learning sparse neural networks via sensitivity-driven regularization. - Enzo Tartaglione; Skjalg Lepsøy; Attilio Fiandrotti; Gianluca Francini (NeurIPS, 2018)

Post-synaptic Potential Regularization Has Potential. - Enzo Tartaglione; Daniele Perlo; Marco Grangetto (ICANN (2), 2019)

Take a Ramble into Solution Spaces for Classification Problems in Neural Networks. - Enzo Tartaglione; Marco Grangetto (ICIAP (1), 2019)

Pruning Artificial Neural Networks: A Way to Find Well-Generalizing, High-Entropy Sharp Minima. - Enzo Tartaglione; Andrea Bragagnolo; Marco Grangetto (ICANN (2), 2020)

Delving in the loss landscape to embed robust watermarks into neural networks. - Enzo Tartaglione; Marco Grangetto; Davide Cavagnino; Marco Botta (ICPR, 2020)

A non-discriminatory approach to ethical deep learning. - Enzo Tartaglione; Marco Grangetto (TrustCom, 2020)

Unveiling COVID-19 from Chest X-ray with deep learning: a hurdles race with small data. - Enzo Tartaglione; Carlo Alberto Barbano; Claudio Berzovini; Marco Calandri; Marco Grangetto (CoRR, 2020)

EnD: Entangling and Disentangling Deep Representations for Bias Correction. - Enzo Tartaglione; Carlo Alberto Barbano; Marco Grangetto (CVPR, 2021)

Capsule Networks with Routing Annealing. - Riccardo Renzulli; Enzo Tartaglione; Attilio Fiandrotti; Marco Grangetto (ICANN (1), 2021)

Bridging the gap between debiasing and privacy for deep learning. - Carlo Alberto Barbano; Enzo Tartaglione; Marco Grangetto (ICCVW, 2021)

Unitopatho, A Labeled Histopathological Dataset for Colorectal Polyps Classification and Adenoma Dysplasia Grading. - Carlo Alberto Barbano; Daniele Perlo; Enzo Tartaglione; Attilio Fiandrotti; Luca Bertero; Paola Cassoni; Marco Grangetto (ICIP, 2021)

On the Role of Structured Pruning for Neural Network Compression. - Andrea Bragagnolo; Enzo Tartaglione; Attilio Fiandrotti; Marco Grangetto (ICIP, 2021)

A Hitchhiker's Guide towards Transactive Memory System Modeling in Small Group Interactions. - Enzo Tartaglione; Béatrice Biancardi; Maurizio Mancini; Giovanna Varni (ICMI Companion, 2021)

Dysplasia Grading of Colorectal Polyps Through Convolutional Neural Network Analysis of Whole Slide Images. - Daniele Perlo; Enzo Tartaglione; Paola Cassoni; Luca Bertero; Marco Grangetto (MICAD, 2021)

Neural Network-derived perfusion maps: a Model-free approach to computed tomography perfusion in patients with acute ischemic stroke. - Umberto A. Gava; Federico D'Agata; Enzo Tartaglione; Marco Grangetto; Francesca Bertolino; Ambra Santonocito; Edwin Bennink; Mauro Bergui (CoRR, 2021)

A two-step explainable approach for COVID-19 computer-aided diagnosis from chest x-ray images. - Carlo Alberto Barbano; Enzo Tartaglione; Claudio Berzovini; Marco Calandri; Marco Grangetto (CoRR, 2021)

Dysplasia grading of colorectal polyps through CNN analysis of WSI. - Daniele Perlo; Enzo Tartaglione; Luca Bertero; Paola Cassoni; Marco Grangetto (CoRR, 2021)

HEMP: High-order entropy minimization for neural network compression. - Enzo Tartaglione; Stéphane Lathuilière; Attilio Fiandrotti; Marco Cagnazzo; Marco Grangetto (Neurocomputing, 2021)

UNITOPATHO. - Luca Bertero; Carlo Alberto Barbano; Daniele Perlo; Enzo Tartaglione; Paola Cassoni; Marco Grangetto; Attilio Fiandrotti; Alessandro Gambella; Luca Cavallo (IEEE DataPort, 2021)

UniToBrain Dataset. - Umberto A. Gava; Federico D'Agata; Edwin Bennink; Enzo Tartaglione; Daniele Perlo; Annamaria Vernone; Francesca Bertolino; Eleonora Ficiarà; Alessandro Cicerale; Fabrizio Pizzagalli; Caterina Guiot; Marco Grangetto; et al. (Zenodo, 2021)

UniToBrain Dataset. - Umberto A. Gava; Federico D'Agata; Edwin Bennink; Enzo Tartaglione; Annamaria Vernone; Francesca Bertolino; Eleonora Ficiarà; Alessandro Cicerale; Fabrizio Pizzagalli; Caterina Guiot; Marco Grangetto; Mauro Bergui (Zenodo, 2021)

UniToBrain Dataset. - Umberto A. Gava; Federico D'Agata; Edwin Bennink; Enzo Tartaglione; Annamaria Vernone; Francesca Bertolino; Eleonora Ficiarà; Alessandro Cicerale; Fabrizio Pizzagalli; Caterina Guiot; Marco Grangetto; Mauro Bergui (Zenodo, 2021)

UniToBrain Dataset. - Umberto A. Gava; Federico D'Agata; Edwin Bennink; Enzo Tartaglione; Annamaria Vernone; Francesca Bertolino; Eleonora Ficiarà; Alessandro Cicerale; Fabrizio Pizzagalli; Caterina Guiot; Marco Grangetto; Mauro Bergui (Zenodo, 2021)

UniToBrain Dataset. - Umberto A. Gava; Federico D'Agata; Edwin Bennink; Enzo Tartaglione; Annamaria Vernone; Francesca Bertolino; Eleonora Ficiarà; Alessandro Cicerale; Fabrizio Pizzagalli; Caterina Guiot; Marco Grangetto; Mauro Bergui (Zenodo, 2021)

UniTOBrain. - Umberto A. Gava; Federico D'Agata; Edwin Bennink; Enzo Tartaglione; Daniele Perlo; Annamaria Vernone; Francesca Bertolino; Eleonora Ficiarà; Alessandro Cicerale; Fabrizio Pizzagalli; Caterina Guiot; Marco Grangetto; et al. (IEEE DataPort, 2021)

The DeepHealth Toolkit: A Key European Free and Open-Source Software for Deep Learning and Computer Vision Ready to Exploit Heterogeneous HPC and Cloud Architectures. - Marco Aldinucci; David Atienza; Federico Bolelli; Mónica Caballero; Iacopo Colonnelli; José Flich; Jon Ander Gómez; David González; Costantino Grana; Marco Grangetto; Simone Leo; Pedro López 001; et al. (Technologies and Applications for Big Data Value, 2022)

Information Removal at the bottleneck in Deep Neural Networks. - Enzo Tartaglione (BMVC, 2022)

A Two-Step Radiologist-Like Approach for Covid-19 Computer-Aided Diagnosis from Chest X-Ray Images. - Carlo Alberto Barbano; Enzo Tartaglione; Claudio Berzovini; Marco Calandri; Marco Grangetto (ICIAP (1), 2022)

UniToBrain Dataset: A Brain Perfusion Dataset. - Daniele Perlo; Enzo Tartaglione; Umberto A. Gava; Federico D'Agata; Edwin Benninck; Mauro Bergui (ICIAP Workshops (1), 2022)

The Rise of the Lottery Heroes: Why Zero-Shot Pruning is Hard. - Enzo Tartaglione (ICIP, 2022)

To update or not to update? Neurons at equilibrium in deep models. - Andrea Bragagnolo; Enzo Tartaglione; Marco Grangetto (NeurIPS, 2022)

REM: Routing Entropy Minimization for Capsule Networks. - Riccardo Renzulli; Enzo Tartaglione; Marco Grangetto (CoRR, 2022)

Disentangling private classes through regularization. - Enzo Tartaglione; Francesca Gennari; Marco Grangetto (CoRR, 2022)

LOss-Based SensiTivity rEgulaRization: Towards deep sparse neural networks. - Enzo Tartaglione; Andrea Bragagnolo; Attilio Fiandrotti; Marco Grangetto (Neural Networks, 2022)

SeReNe: Sensitivity-Based Regularization of Neurons for Structured Sparsity in Neural Networks. - Enzo Tartaglione; Andrea Bragagnolo; Francesco Odierna; Attilio Fiandrotti; Marco Grangetto (IEEE Trans. Neural Networks Learn. Syst., 2022)

A Hitchhiker's Guide to White-Box Neural Network Watermarking Robustness. - Carl De Sousa Trias; Mihai Mitrea; Enzo Tartaglione; Attilio Fiandrotti; Marco Cagnazzo; Sumanta Chaudhuri (EUVIP, 2023)

All Predictions Matter: an Online Video Prediction Approach. - Melan Vijayaratnam; Marco Cagnazzo; Giuseppe Valenzise; Enzo Tartaglione (EUVIP, 2023)

Mining bias-target Alignment from Voronoi Cells. - Rémi Nahon; Van-Tam Nguyen; Enzo Tartaglione (ICCV, 2023)

SCoTTi: Save Computation at Training Time with an adaptive framework. - Ziyu Li; Enzo Tartaglione; Van-Tam Nguyen (ICCV (Workshops), 2023)

Can Unstructured Pruning Reduce the Depth in Deep Neural Networks? - Zhu Liao; Victor Quétu; Van-Tam Nguyen; Enzo Tartaglione (ICCV (Workshops), 2023)

Shannon Strikes Again! Entropy-based Pruning in Deep Neural Networks for Transfer Learning under Extreme Memory and Computation Budgets. - Gabriele Spadaro; Riccardo Renzulli; Andrea Bragagnolo; Jhony H. Giraldo; Attilio Fiandrotti; Marco Grangetto; Enzo Tartaglione (ICCV (Workshops), 2023)

A Differentiable Entropy Model for Learned Image Compression. - Alberto Presta; Attilio Fiandrotti; Enzo Tartaglione; Marco Grangetto (ICIAP (1), 2023)

Sparse Double Descent in Vision Transformers: Real or Phantom Threat? - Victor Quétu; Marta Milovanovic; Enzo Tartaglione (ICIAP (2), 2023)

Two is Better than One: Achieving High-Quality 3D Scene Modeling with a NeRF Ensemble. - Francesco Di Sario; Riccardo Renzulli; Enzo Tartaglione; Marco Grangetto (ICIAP (2), 2023)

Dodging the Double Descent in Deep Neural Networks. - Victor Quétu; Enzo Tartaglione (ICIP, 2023)

Unbiased Supervised Contrastive Learning. - Carlo Alberto Barbano; Benoit Dufumier; Enzo Tartaglione; Marco Grangetto; Pietro Gori (ICLR, 2023)

Packed Ensembles for efficient uncertainty estimation. - Olivier Laurent 002; Adrien Lafage; Enzo Tartaglione; Geoffrey Daniel; Jean-Marc Martinez; Andrei Bursuc; Gianni Franchi (ICLR, 2023)

Learn How to Prune Pixels for Multi-View Neural Image-Based Synthesis. - Marta Milovanovic; Enzo Tartaglione; Marco Cagnazzo; Félix Henry (ICME Workshops, 2023)

A round-trip journey in pruned artificial neural networks. - Andrea Bragagnolo; Enzo Tartaglione; Gianluca Dalmasso; Marco Grangetto (Ital-IA, 2023)

Mental State Classification Using EEG Signals: Ethics, Law and Challenges. - Rémi Nahon; Nasim Bagheri; Giovanna Varni; Enzo Tartaglione; Van-Tam Nguyen (PKDD/ECML Workshops (1), 2023)

AIoT-based Neural Decoding and Neurofeedback for Accelerated Cognitive Training: Vision, Directions and Preliminary Results. - Van-Tam Nguyen; Enzo Tartaglione; Tuan Dinh (SSP, 2023)

Optimized preprocessing and Tiny ML for Attention State Classification. - Yinghao Wang; Rémi Nahon; Enzo Tartaglione; Pavlo Mozharovskyi; Van-Tam Nguyen (SSP, 2023)

Unified Measures for the Rate-Distortion-Latency Trade-off. - Melan Vijayaratnam; Marta Milovanovic; Marco Cagnazzo; Enzo Tartaglione; Giuseppe Valenzise (VCIP, 2023)

Compressing Explicit Voxel Grid Representations: fast NeRFs become also small. - Chenxi Lola Deng; Enzo Tartaglione (WACV, 2023)

Dodging the Sparse Double Descent. - Victor Quétu; Enzo Tartaglione (CoRR, 2023)

Rethinking Class-incremental Learning in the Era of Large Pre-trained Models via Test-Time Adaptation. - Imad Eddine Marouf; Subhankar Roy; Enzo Tartaglione; Stéphane Lathuilière (CoRR, 2023)

SCoTTi: Save Computation at Training Time with an adaptive framework. - Ziyu Lin; Enzo Tartaglione; Van-Tam Nguyen (CoRR, 2023)

Neural network-derived perfusion maps: A model-free approach to computed tomography perfusion in patients with acute ischemic stroke. - Umberto A. Gava; Federico D'Agata; Enzo Tartaglione; Riccardo Renzulli; Marco Grangetto; Francesca Bertolino; Ambra Santonocito; Edwin Bennink; Giacomo Vaudano; Andrea Boghi; Mauro Bergui (Frontiers Neuroinformatics, 2023)

Disentangling private classes through regularization. - Enzo Tartaglione; Francesca Gennari; Victor Quétu; Marco Grangetto (Neurocomputing, 2023)

From Model Complexity Reduction to Feature Selection in Deep Learning: a Regularization Story. (De la réduction de la complexité des modèles à la sélection des caractéristiques dans l'apprentissage profond : une histoire de régularisation). - Enzo Tartaglione (2024)

DSD²: Can We Dodge Sparse Double Descent and Compress the Neural Network Worry-Free? - Victor Quétu; Enzo Tartaglione (AAAI, 2024)

Find the Lady: Permutation and Re-synchronization of Deep Neural Networks. - Carl De Sousa Trias; Mihai Petru Mitrea; Attilio Fiandrotti; Marco Cagnazzo; Sumanta Chaudhuri; Enzo Tartaglione (AAAI, 2024)

Trimming the Fat: Efficient Compression of 3D Gaussian Splats through Pruning. - Muhammad Salman Ali; Maryam Qamar; Sung-Ho Bae; Enzo Tartaglione (BMVC, 2024)

Domain Adaptation for Learned Image Compression with Supervised Adapters. - Alberto Presta; Gabriele Spadaro; Enzo Tartaglione; Attilio Fiandrotti; Marco Grangetto (DCC, 2024)

Memory-Optimized Once-For-All Network. - Maxime Girard; Victor Quétu; Samuel Tardieu; Van-Tam Nguyen; Enzo Tartaglione (ECCV Workshops (11), 2024)

Weighted Ensemble Models Are Strong Continual Learners. - Imad Eddine Marouf; Subhankar Roy; Enzo Tartaglione; Stéphane Lathuilière (ECCV (71), 2024)

Debiasing Surgeon: Fantastic Weights and How to Find Them. - Rémi Nahon; Ivan Luiz De Moura Matos; Van-Tam Nguyen; Enzo Tartaglione (ECCV (85), 2024)

Boost Your NeRF: A Model-Agnostic Mixture of Experts Framework for High Quality and Efficient Rendering. - Francesco Di Sario; Riccardo Renzulli; Enzo Tartaglione; Marco Grangetto (ECCV (83), 2024)

Gabic: Graph-Based Attention Block for Image Compression. - Gabriele Spadaro; Alberto Presta; Enzo Tartaglione; Jhony H. Giraldo; Marco Grangetto; Attilio Fiandrotti (ICIP, 2024)

WaterMAS: Sharpness-Aware Maximization for Neural Network Watermarking. - Carl De Sousa Trias; Mihai Mitrea; Attilio Fiandrotti; Marco Cagnazzo; Sumanta Chaudhuri; Enzo Tartaglione (ICPR (5), 2024)

Activation Map Compression through Tensor Decomposition for Deep Learning. - Le-Trung Nguyen; Aël Quélennec; Enzo Tartaglione; Samuel Tardieu; Van-Tam Nguyen (NeurIPS, 2024)

The Simpler The Better: An Entropy-Based Importance Metric to Reduce Neural Networks' Depth. - Victor Quétu; Zhu Liao; Enzo Tartaglione (ECML/PKDD (6), 2024)

ALICE: Adapt your Learnable Image Compression modEl for variable bitrates. - Gabriele Spadaro; Muhammad Salman Ali; Alberto Presta; Giommaria Pilo; Sung-Ho Bae; Jhony H. Giraldo; Attilio Fiandrotti; Marco Grangetto; Enzo Tartaglione (VCIP, 2024)

Mini but Mighty: Finetuning ViTs with Mini Adapters. - Imad Eddine Marouf; Enzo Tartaglione; Stéphane Lathuilière (WACV, 2024)

Towards On-Device Learning on the Edge: Ways to Select Neurons to Update Under a Budget Constraint. - Aël Quélennec; Enzo Tartaglione; Pavlo Mozharovskyi; Van-Tam Nguyen (WACV (Workshops), 2024)

NEPENTHE: Entropy-Based Pruning as a Neural Network Depth's Reducer. - Zhu Liao; Victor Quétu; Van-Tam Nguyen; Enzo Tartaglione (CoRR, 2024)

LaCoOT: Layer Collapse through Optimal Transport. - Victor Quétu; Nour Hezbri; Enzo Tartaglione (CoRR, 2024)

Say My Name: a Model's Bias Discovery Framework. - Massimiliano Ciranni; Luca Molinaro; Carlo Alberto Barbano; Attilio Fiandrotti; Vittorio Murino; Vito Paolo Pastore; Enzo Tartaglione (CoRR, 2024)

HYGENE: A Diffusion-Based Hypergraph Generation Method. - Dorian Gailhard; Enzo Tartaglione; Lirida Naviner; Jhony H. Giraldo (AAAI, 2025)

Till the Layers Collapse: Compressing a Deep Neural Network Through the Lenses of Batch Normalization Layers. - Zhu Liao; Nour Hezbri; Victor Quétu; Van-Tam Nguyen; Enzo Tartaglione (AAAI, 2025)

ELMGS: Enhancing Memory and Computation Scalability Through coMpression for 3D Gaussian Splatting. - Muhammad Salman Ali; Sung-Ho Bae; Enzo Tartaglione (WACV, 2025)

Efficient Progressive Image Compression with Variance-Aware Masking. - Alberto Presta; Enzo Tartaglione; Attilio Fiandrotti; Marco Grangetto; Pamela C. Cosman (WACV, 2025)

WiGNet: Windowed Vision Graph Neural Network. - Gabriele Spadaro; Marco Grangetto; Attilio Fiandrotti; Enzo Tartaglione; Jhony H. Giraldo (WACV, 2025)

LayerFold: A Python library to reduce the depth of neural networks. - Giommaria Pilo; Nour Hezbri; André Pereira e Ferreira; Victor Quétu; Enzo Tartaglione (SoftwareX, 2025)

STanH: Parametric Quantization for Variable Rate Learned Image Compression. - Alberto Presta; Enzo Tartaglione; Attilio Fiandrotti; Marco Grangetto (IEEE Trans. Image Process., 2025)

FOLDER: Accelerating Multi-modal Large Language Models with Enhanced Performance. - Haicheng Wang; Zhemeng Yu; Gabriele Spadaro; Chen Ju; Victor Quétu; Enzo Tartaglione (CoRR, 2025)

GoDe: Gaussians on Demand for Progressive Level of Detail and Scalable Compression. - Francesco Di Sario; Riccardo Renzulli; Marco Grangetto; Akihiro Sugimoto; Enzo Tartaglione (CoRR, 2025)

No Images, No Problem: Retaining Knowledge in Continual VQA with Questions-Only Memory. - Imad Eddine Marouf; Enzo Tartaglione; Stéphane Lathuilière; Joost van de Weijer 001 (CoRR, 2025)

Diffusing DeBias: a Recipe for Turning a Bug into a Feature. - Massimiliano Ciranni; Vito Paolo Pastore; Roberto Di Via; Enzo Tartaglione; Francesca Odone; Vittorio Murino (CoRR, 2025)

Compression in 3D Gaussian Splatting: A Survey of Methods, Trends, and Future Directions. - Muhammad Salman Ali; Chaoning Zhang; Marco Cagnazzo; Giuseppe Valenzise; Enzo Tartaglione; Sung-Ho Bae (CoRR, 2025)

Lightweight Embedded FPGA Deployment of Learned Image Compression with Knowledge Distillation and Hybrid Quantization. - Alaa Mazouz; Sumanta Chaudhuri; Marco Cagnazzo; Mihai Mitrea; Enzo Tartaglione; Attilio Fiandrotti (CoRR, 2025)

Security and Real-time FPGA integration for Learned Image Compression. - Alaa Mazouz; Carl De Sousa Trias; Sumanta Chaudhuri; Attilio Fiandrotti; Marco Cagnazzo; Mihai Mitrea; Enzo Tartaglione (CoRR, 2025)

Efficient Adaptation of Deep Neural Networks for Semantic Segmentation in Space Applications. - Leonardo Olivi; Edoardo Santero Mormile; Enzo Tartaglione (CoRR, 2025)

I-INR: Iterative Implicit Neural Representations. - Ali Haider; Muhammad Salman Ali; Maryam Qamar; Tahir Khalil; Soo Ye Kim; Jihyong Oh; Enzo Tartaglione; Sung-Ho Bae (CoRR, 2025)

Beyond Low-rank Decomposition: A Shortcut Approach for Efficient On-Device Learning. - Le-Trung Nguyen; Aël Quélennec; Van-Tam Nguyen; Enzo Tartaglione (CoRR, 2025)

Denoising Diffusion Probabilistic Model for Point Cloud Compression at Low Bit-Rates. - Gabriele Spadaro; Alberto Presta; Jhony H. Giraldo; Marco Grangetto; Wei Hu; Giuseppe Valenzise; Attilio Fiandrotti; Enzo Tartaglione (CoRR, 2025)

Unsupervised Learning of Unbiased Visual Representations. - Carlo Alberto Barbano; Enzo Tartaglione; Marco Grangetto (IEEE Trans. Artif. Intell., 2025)

Feature-aware Hypergraph Generation via Next-Scale Prediction. - Dorian Gailhard; Enzo Tartaglione; Lirida Naviner; Jhony H. Giraldo (CoRR, 2025)

Neural Velocity for hyperparameter tuning. - Gianluca Dalmasso; Andrea Bragagnolo; Enzo Tartaglione; Attilio Fiandrotti; Marco Grangetto (CoRR, 2025)

Capsule networks do not need to model everything. - Riccardo Renzulli; Enzo Tartaglione; Marco Grangetto (Pattern Recognit., 2026)